Develop and optimize mathematical models of complex systems Show
Mathematical models are critical to understanding and accurately predicting the behavior of complex systems. These models enable critical tasks, such as:
MathWorks products provide all the tools you need to develop mathematical models. MATLAB® supports both numeric and symbolic modeling approaches and provides curve fitting, statistics, optimization, ODE and PDE solving, calculus, and other core mathematical tools. Simulink® adds an environment for modeling and simulating the behavior of multidomain systems and for developing embedded systems.
Building Models from Data and Scientific Principles
With the MATLAB and Simulink product families you can model virtually any type of system, including:
Develop Models from DataWhen you have physical insight, you can create models from first principles using analytic or symbolic approaches. Data-driven modeling techniques are especially useful when you do not have sufficient information about your system. In this case, you can ensure model accuracy by choosing a modeling technique that is right for your experimental or historical data. Use statistics curve fitting tools to explore relationships among your data. You can use linear and nonlinear regression models, classification, clustering, and surface fitting tools. Dynamic models that allow you to express the effect of a system’s past experiences on its current and future behavior can be modeled using neural networks and system identification techniques. Data-driven techniques can also be used to tune the coefficients of your first-principles model in order to fit experimental data using grey-box modeling and response optimization techniques.
Develop Models Based on Mathematical, Engineering, and Scientific PrinciplesYou can choose from multiple approaches for creating mathematical models based on first principles. For example, you can:
Develop Models for Domain-Specific ApplicationsMathWorks application-specific products let you develop mathematical models for applications in the following areas:
Evaluating and Optimizing ModelsAfter developing your model, you can exercise it under different conditions, manage and visualize simulation results, and optimize its fidelity. You can also document your work and share the model with colleagues. Simulate your ModelSimulation lets you predict the behavior of your system for different conditions or validate your model by comparing simulation results to test data. MathWorks tools make it easy to manage all aspects of model simulation. You can:
Optimize your ModelOnce you’ve built your model, you can optimize parameters and validate the model against actual system behavior. MathWorks optimization tools let you refine a model of an existing system or optimize a new system design, by adjusting design variables to meet specific performance criteria. Document and Share your ModelWith MATLAB and Simulink reporting tools you can automatically document model derivation steps and simulation results, and keep these up to date with your design. You can use MathWorks desktop and Web deployment tools to share your optimized models and associated applications with colleagues. What are the two branches of quantitative management?The quantitative management perspective and its two components, management science and operations management, attempt to apply quantitative techniques to decision making and problem solving. These areas are also of considerable importance to contemporary managers.
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